1. Field of the Invention
The present invention relates generally to a Multiple-Input Multiple-Output (MIMO) communication system, and more particularly, to an apparatus and method for generating a high-reliability Log Likelihood Ratio (LLR) in a Spatial Multiplexing (SM) communication system.
2. Description of the Related Art
Demand for various wireless multimedia services has increased significantly due to rapid growth of the wireless mobile communications market and, in particular, improvements in high-capacity and high-rate data transmission are underway. Accordingly, a discovery of a method for efficiently using a limited amount of frequency resources is urgently needed. A new communication scheme using multiple antennas, an example of which is a MIMO communication system using multiple antennas, would be helpful.
A MIMO communication system uses multiple transmit (TX) antennas and multiple receive (RX) antennas. Unlike a single-antenna communication system, a MIMO communication system can increase channel transmission capacity in proportion to the number of antennas even without allocation of additional frequency and TX power. Thus, extensive research is being conducted on MIMO communication schemes.
Multiple-antenna transmission schemes can be broadly classified into a Spatial Diversity (SD) scheme, a Spatial Multiplexing (SM) scheme, and a hybrid thereof. An SD scheme provides a diversity gain corresponding to the number of TX antennas and the number of RX antennas, thereby increasing transmission reliability. An SM scheme transmits a plurality of data streams simultaneously, thereby increasing a data transmission rate.
When TX antennas transmit different data streams using an SM scheme, a mutual interference occurs between the simultaneously-transmitted data streams. Accordingly, a corresponding receiver detects a received signal using a Maximum Likelihood (ML) scheme considering the interference effect, or detects the received signal after removal of the interference. For example, the interference is removed using a Zero Forcing (ZF) scheme or a Minimum Mean Square Error (MMSE) scheme. In a general SM scheme, the performance of a receiver has a trade-off relationship with computational complexity of the receiver. Thus, extensive research is being conducted to provide a reception process that can approach the performance of an ML receiver while reducing the computational complexity of the receiver.
As is known in the art, an SM receiver provides good performance when a Soft DECision (SDEC) value, instead of a Hard DECision (HDEC) value, of an encoded bit is inputted to a channel decoder. The input SDEC value of the channel decoder is an estimated value of a modulated symbol transmitted over a channel, which uses a Log Likelihood Ratio (LLR) value. Therefore, an SM receiver uses not only a low-complexity reception process but also a process for generating an optimal LLR from the reception process.
A definition is given of a system model in consideration of a system that includes NT number of TX antennas and NR number of RX antennas as illustrated in FIG. 1. When a TX signal (or a modulated signal) to be transmitted through each TX antenna is denoted by di, an RX signal r of a receiver can be expressed as Equation (1) below. It is assumed that the signal di transmitted through each TX antenna is an M-Quadrature Amplitude Modulation (QAM) signal. In this case, the number of encoded bits that can be simultaneously transmitted is NT×log2(M).r=Hd+n  (1)where r is an RX signal vector, d is a TX symbol vector, n is an ambient Gaussian noise vector, and H is a coefficient matrix of a channel established between the TX antenna and the RX antenna. The channel coefficient matrix H is defined as Equation (2):
                              d          =                                    [                                                d                  1                                ,                                  d                  2                                ,                                  d                  3                                ,                …                ⁢                                                                  ,                                  d                                      N                    T                                                              ]                        T                          ⁢                                  ⁢                  r          =                                    [                                                r                  1                                ,                                  r                  2                                ,                                  r                  3                                ,                …                ⁢                                                                  ,                                  r                                      N                    R                                                              ]                        T                          ⁢                                  ⁢                  H          =                      [                                                                                h                    11                                                                                        h                    12                                                                    ⋯                                                                      h                                          1                      ⁢                                              N                        R                                                                                                                                                              h                    21                                                                                        h                    22                                                                    ⋯                                                                      h                                          2                      ⁢                                              N                        R                                                                                                                                          ⋮                                                  ⋮                                                  ⋯                                                  ⋮                                                                                                  h                                                                  N                        T                                            ⁢                      1                                                                                                            h                                                                  N                        T                                            ⁢                      2                                                                                        ⋯                                                                      h                                                                  N                        T                                            ⁢                                              N                        R                                                                                                                  ]                                              (        2        )            where the channel coefficient matrix H is an NT×NR matrix in which an (i,j) element hij denotes a channel response between the ith TX antenna and the jth RX antenna.
Signal detection methods according to the above SM scheme can be summarized as follows:
First, an ML scheme uses Equation (3) below to calculate Euclidean distances for all symbols (or signal points) within a constellation and then selects a symbol with the shortest straight distance. That is, the ML scheme determines a distance between y and Hx to determine a symbol with the shortest distance to be a symbol with the highest similarity (i.e., a symbol with the smallest error). However, the ML scheme must calculate Euclidean distances for MNT (M: a modulation level) number of vectors. Therefore, the ML scheme exponentially increases in complexity and thus is difficult to implement.{circumflex over (x)}=argxmin∥y−HX∥F2  (3)
A Successive Interference Cancellation (SIC) scheme reconstructs HDEC values of a previous stage to remove interference from an RX signal. However, when there is an error in the HDEC values of the previous stage of the SIC scheme, the error is weighted in the next stage. In this case, the reliability of the HDEC values decreases with the progress of each subsequent stage.
Therefore, the SIC scheme needs to consider error propagation causing performance degradation. That is, because decoding operations are performed in the order of TX antenna indexes regardless of channel conditions, the interference cancellation process is performed without removal of a TX antenna with high signal strength. Thus, the performance of a TX antenna with low signal strength is not greatly improved. A Vertical Bell Labs LAyered Space-Time (V-BLAST) scheme is an improved process for solving the above problem. The V-BLAST scheme performs an interference cancellation process in the descending order of the signal strengths of TX antennas and thus has better performance than the SIC scheme.
A Modified ML (MML) scheme uses the ML scheme to decode symbols transmittable from all TX antennas except a particular TX antenna. A signal transmitted from the particular TX antenna is determined using a simple slicing function Q ( ) expressed as Equation (4) below. The MML scheme has the same performance as the ML scheme, and its computational complexity is expressed as the exponential multiplication of the subtraction of 1 from the number of the TX antennas. That is, while the ML scheme calculates Euclidean distances for MNT number of vectors, the MML scheme calculates Euclidean distances for MNT−1 number of vectors and detects signals for the remaining symbols using the slicing function.
                              x          i                =                  Q          (                                                    h                i                H                                                                                                    h                    i                                                                    2                                      ⁢                          (                              y                -                                                      ∑                                          j                      ≠                      i                                                        ⁢                                                            h                      j                                        ⁢                                          x                      j                                                                                  )                                )                                    (        4        )            
A proposed Recursive MML (RMML) scheme reduces the complexity of the MML scheme. Using Givens rotation, the RMML scheme nulls a channel to generate several small channels (subsystems), and makes a decision on the minimum unit of 2×2 channels according to the MML scheme. In this manner, the RMML scheme generates several (e.g., 3×3 and 2×2) subsystems, thereby reducing the computational complexity while providing performance that approaches the performance of the ML scheme. However, the generation of several subsystems means the presence of several candidate TX vectors, which limits the complexity reduction. In addition, like the SIC scheme, the RMML scheme causes performance degradation due to error propagation because the 2×2 subsystems make an immediate decision.
Meanwhile, when ML receivers are used in an MIMO communication system using two TX antennas, the optimal LLR can be expressed as Equation (5):
                                          LLR            ⁡                          (                              b                                  1                  ,                  i                                            )                                =                      log            (                                                            ∑                                      c                    ∈                                          C                      i                      +                                                                      ⁢                                                      ∑                                                                  d                        2                                            ∈                      C                                                        ⁢                                      exp                    (                                          -                                                                                                                                                              r                              -                                                                                                h                                  1                                                                ⁢                                c                                                            -                                                                                                h                                  2                                                                ⁢                                                                  d                                  2                                                                                                                                                                          2                                                                          2                          ⁢                                                      σ                            2                                                                                                                )                                                                                                ∑                                      c                    ∈                                          C                      i                      -                                                                      ⁢                                                      ∑                                                                  d                        2                                            ∈                      C                                                        ⁢                                      exp                    (                                          -                                                                                                                                                              r                              -                                                                                                h                                  1                                                                ⁢                                c                                                            -                                                                                                h                                  2                                                                ⁢                                                                  d                                  2                                                                                                                                                                          2                                                                          2                          ⁢                                                      σ                            2                                                                                                                )                                                                        )                          ⁢                                  ⁢                              LLR            ⁡                          (                              b                                  2                  ,                  i                                            )                                =                      log            (                                                            ∑                                      c                    ∈                                          C                      i                      +                                                                      ⁢                                                      ∑                                                                  d                        1                                            ∈                      C                                                        ⁢                                      exp                    (                                          -                                                                                                                                                              r                              -                                                                                                h                                  1                                                                ⁢                                                                  d                                  1                                                                                            -                                                                                                h                                  2                                                                ⁢                                c                                                                                                                                          2                                                                          2                          ⁢                                                      σ                            2                                                                                                                )                                                                                                ∑                                      c                    ∈                                          C                      i                      -                                                                      ⁢                                                      ∑                                                                  d                        1                                            ∈                      C                                                        ⁢                                      exp                    (                                          -                                                                                                                                                              r                              -                                                                                                h                                  1                                                                ⁢                                                                  d                                  1                                                                                            -                                                                                                h                                  2                                                                ⁢                                c                                                                                                                                          2                                                                          2                          ⁢                                                      σ                            2                                                                                                                )                                                                        )                                              (        5        )            where bj,i denotes the ith bit of the jth antenna, Ci+ denotes a set of di's whose ith bit is ‘+1’, and Ci− denotes a set of di's whose ith bit is ‘−1’.
As can be seen from Equation (5), because Euclidean distances must be calculated with respect to all possible combinations of TX signals, the LLR calculation in the ML receiver is difficult to implement for a modulation scheme with a high modulation level or many antennas.
A receiver structure is therefore needed that can implement an SM scheme with high reliability similar to that of an LLR in an ML scheme while having low complexity.